605,620 research outputs found
The influence of task contexts on the decision-making of humans and computers.
Many environments in which people and computer agents interact involve deploying resources to accomplish tasks and satisfy goals. This paper investigates the way that the context in which decisions are made affects the behavior of people and the performance of computer agents that interact with people in such environments. It presents experiments that measured negotiation behavior in two different types of settings. One setting was a task context that made explicit the relationships among goals, (sub)tasks and resources. The other setting was a completely abstract context in which only the payoffs for the decision choices were listed. Results show that people are more helpful, less selfish, and less competitive when making decisions in task contexts than when making them in completely abstract contexts. Further, their overall performance was better in task contexts. A predictive computational model that was trained on data obtained in the task context outperformed a model that was trained under the abstract context. These results indicate that taking context into account is essential for the design of computer agents that will interact well with people.Engineering and Applied Science
Macroscopes: models for collective decision making
We introduce a new model of collective decision making, when a global
decision needs to be made but the parties only possess partial information, and
are unwilling (or unable) to first create a globalcomposite of their local
views. Our macroscope model captures two key features of many real-world
problems: allotment structure (how access to local information is apportioned
between parties, including overlaps between the parties) and the possible
presence of meta-information (what each party knows about the allotment
structure of the overall problem). Using the framework of communication
complexity, we formalize the efficient solution of a macroscope. We present
general results about the macroscope model, and also results that abstract the
essential computational operations underpinning practical applications,
including in financial markets and decentralized sensor networks. We illustrate
the computational problem inherent in real-world collective decision making
processes using results for specific functions, involving detecting a change in
state (constant and step functions), and computing statistical properties (the
mean).Comment: Presented at Collective Intelligence conference, 2012
(arXiv:1204.2991), 8 page
Simplifying the Puzzle: How Computational Thinking and Abstraction Can Help Teachers Conquer Classroom Complexity
The investigation examines the utilization of abstraction and computational thinking by educators to effectively navigate the complexities encountered in the educational setting. It underscores the significance of these cognitive capacities in the examination and determination of intricate issues. To facilitate students in problem-solving and decision-making, educators can utilize computational thinking to break down challenging issues into more manageable components. Two capacities that educators can utilize to apply their knowledge in various circumstances are the identification of patterns and the extrapolation of abstract notions. This research study demonstrated the utility of abstraction and computational thinking in equipping educators with the necessary tools to address classroom issues, which is particularly valuable for curricula focused on training future educators. The study not only identifies potential challenges but also offers recommendations for overcoming the difficulties that teachers may encounter when implementing these ideas in the classroom. By employing these tactics and recommended solutions, educators can help students improve their analytical, problem-solving, and critical thinking abilities, thus preparing them for the challenges of the digital era
Rossler Nonlinear Dynamical Machine for Cryptography Applications
In many of the cryptography applications like password or IP address
encryption schemes, symmetric cryptography is useful. In these relatively
simpler applications of cryptography, asymmetric cryptography is difficult to
justify on account of the computational and implementation complexities
associated with asymmetric cryptography. Symmetric schemes make use of a single
shared key known only between the two communicating hosts. This shared key is
used both for the encryption as well as the decryption of data. This key has to
be small in size besides being a subset of a potentially large keyspace making
it convenient for the communicating hosts while at the same time making
cryptanalysis difficult for the potential attackers. In the present work, an
abstract Rossler nonlinear dynamical machine has been described first. The
Rossler system exhibits chaotic dynamics for certain values of system
parameters and initial conditions. The chaotic dynamics of the Rossler system
with its apparently erratic and irregular characteristics and extreme
sensitivity to the initial conditions has been used for the design of the
cryptographic key in an attempt to increase the confusion and the challenge for
the potential attackers.Comment: 5 pages, 3 figure
The Profiling Potential of Computer Vision and the Challenge of Computational Empiricism
Computer vision and other biometrics data science applications have commenced
a new project of profiling people. Rather than using 'transaction generated
information', these systems measure the 'real world' and produce an assessment
of the 'world state' - in this case an assessment of some individual trait.
Instead of using proxies or scores to evaluate people, they increasingly deploy
a logic of revealing the truth about reality and the people within it. While
these profiling knowledge claims are sometimes tentative, they increasingly
suggest that only through computation can these excesses of reality be captured
and understood. This article explores the bases of those claims in the systems
of measurement, representation, and classification deployed in computer vision.
It asks if there is something new in this type of knowledge claim, sketches an
account of a new form of computational empiricism being operationalised, and
questions what kind of human subject is being constructed by these
technological systems and practices. Finally, the article explores legal
mechanisms for contesting the emergence of computational empiricism as the
dominant knowledge platform for understanding the world and the people within
it
Detection of channel variations to improve channel estimation methods
“The final publication is available at Springer via http://dx.doi.org/[10.1007/s00034-014-9767-8]”[Abstract] In current digital communication systems, channel information is typically
acquired by supervised approaches that use pilot symbols included in the transmit
frames. Given that pilot symbols do not convey user data, they penalize throughput
spectral efficiency, and transmit energy consumption of the system. Unsupervised
channel estimation algorithms could be used to mitigate the aforementioned drawbacks
although they present higher computational complexity than that offered by
supervised ones. This paper proposes a simple decision method suitable for slowly
varying channels to determine whether the channel has suffered a significant variation,
which requires to estimate the matrix of the recently changed channel. Otherwise, a
previous estimate is used to recover the transmitted symbols. The main advantage of
this method is that the decision criterion is only based on information acquired during
the time frame synchronization, which is carried out at the receiver. We show that the
proposed criterion provides a considerable improvement of computational complexity
for both supervised and unsupervised methods, without incurring in a penalization in
terms of symbol error ratio. Specifically, we consider systems that make use of the popular
Alamouti code. Performance evaluation is accomplished by means of simulated
channels as well as making use of indoor wireless channels measured using a testbed
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